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Record W2160140118 · doi:10.1109/tec.2011.2180171

Filtering of Hall-Sensor Signals for Improved Operation of Brushless DC Motors

2012· article· en· W2160140118 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Energy Conversion · 2012
Typearticle
Languageen
FieldEngineering
TopicSensorless Control of Electric Motors
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHall effect sensorDC motorBrushed DC electric motorInverterComputer scienceElectrical engineeringElectric motorWork (physics)Control theory (sociology)Control engineeringElectronic engineeringEngineeringAC motorVoltageMagnetControl (management)Mechanical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Brushless dc motors controlled by Hall-effect sensors are used in variety of applications, wherein the Hall sensors should be placed 120 electrical degrees apart. This is difficult to achieve in practice especially in low-precision motors, which leads to unsymmetrical operation of the inverter/motor phases. To mitigate this phenomenon, an approach of filtering the Hall-sensor signals has been recently proposed. This letter extends the previous work and presents a very efficient digital implementation of such filters that can be easily included into various brushless dc motor-drive systems for restoring their operation in steady state and transients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.784
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.209
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it